MAS6011 Dependent Data

The unit develops concepts and techniques for the analysis of data having the complex structure typical of many real applications. The two main themes are the analysis of observations on several dependent variables, and the analysis of dependent observations made over a period of time on a single variable. The unit begins with a practical introduction to multivariate analysis: Data Mining techniques such as summarizing and displaying high dimensional data and dimensionality reduction, principal components, multidimensional scaling, multivariate analysis of variance and discrimination. A review of repeated measures problems links to ideas of time series analysis. General techniques for the study of time series are developed, including structural descriptions, Box-Jenkins and state-space models and their fitting, and techniques for forecasting, covering local level, trend and seasonal time series. Emphasis is given to the practical implementation of the techniques using appropriate computer packages.

There are no prerequisites for this module.
No other modules have this module as a prerequisite.